Empirical research
Detecting Risk of Low Health Literacy in Disadvantaged Populations Using Area-based Measures
Authors:
Andrew J. Knighton ,
Intermountain Healthcare, US
Kimberly D. Brunisholz,
Intermountain Healthcare, US
Samuel T. Savitz
University of North Carolina at Chapel Hill, US
Abstract
Introduction: Socio-economic status (SES) and low health literacy (LHL) are closely correlated. Both are directly associated with clinical and behavioral risk factors and healthcare outcomes. Learning healthcare systems are introducing small-area measures to address the challenges associated with maintaining patient-reported measures of SES and LHL. This study’s purpose was to measure the association between two available census block measures associated with SES and LHL. Understanding the relationship can guide the identification of a multi-purpose area based measure for delivery system use.
Methods: A retrospective observational design was deployed using all US Census block groups in Utah. The principal dependent variable was a nationally-standardized health literacy score (HLS). The primary explanatory variable was a state-standardized area deprivation index (ADI). Statistical methods included linear regression and tests of association. Receiver operating characteristic (ROC) analysis was used to develop LHL criteria using ADI.
Results: A significant negative association between the HLS and the ADI score remained after adjusting for area-level risk factors (β: –0.21 (95% CI: –0.22, –0.19) p < .001). Eighteen block groups (<1%) were identified as having LHL using HLS. A combination of three or more ADI components correlated with LHL predicted 78% of HLS LHL block groups and 35 additional block groups not identified using HLS (c-statistic: 0.64; 95% CI: 0.62, 0.66).
Conclusions: HLS and ADI use differing measurement criteria but are closely correlated. A state-based ADI detected additional neighborhoods with risk of LHL compared to use of a national HLS. An ADI represents a multi-purpose area measure of social determinants useful for learning health systems tailoring care.
How to Cite:
Knighton AJ, Brunisholz KD, Savitz ST. Detecting Risk of Low Health Literacy in Disadvantaged Populations Using Area-based Measures. eGEMs (Generating Evidence & Methods to improve patient outcomes). 2017;5(3):7. DOI: http://doi.org/10.5334/egems.191
